Neuron Explorer

Qwen3-0.6B

'sub' starting a word fragment

A neuron in layer 26 of Qwen3-0.6B. Its strongest snippets are very consistent: they mostly peak on the same token. It is featured, so it has steering outputs.

What this neuron does

This neuron fires most strongly on the piece 'sub' when it starts a longer word split across tokens, as in subcutaneous, subordinated or subunit. Turning it up made the model's text drift into unrelated topics, so it doesn't seem to steer the subject in any clear way.

Written by Claude from this neuron's activations and steering outputs. Confidence: medium. Think it is wrong? Flag it (opens a prefilled issue on GitHub).

Fires most on

The text windows where this neuron's activation was highest. Amber marks positive activation; the outlined token is the peak. Hover a token for its strength.

  1. #1 peak

    called lean gene is not only linked to the risk of diabetes type 2 but also that of heart disease.⏎This gene IRS1 does lower fat, but only subcutaneous fat – fat under the skin, and not visceral fat, the fat

  2. #2 peak

    organic chemistry laboratory for cooling reactions to sub-zero temperatures. Instead of using ice water to cool to 0 C, you

  3. #3 peak

    in which the expectations are found are more⏎difficult. They will require a sophistication in manipulating⏎integrals, changing variables in integrals and using the Erf or⏎CumNorm functions. This would be a good task to use in this way

  4. #4 peak

    only obstacle between the West and the fabulous contracts offered by Russia. All other matters should be subordinated to the trade—it’s a highly compelling argument.⏎The third thread paradoxically

  5. #5 peak

    the plane after Kitaigorodsky . The upper arrangement has p2 plane group with twofold rotation, and the lower arrangement has pmm plane group with symmetry planes. In a complementary arrangement, the protrusion of one molecule complements

  6. #6 peak

    of the muon (μ−⏎) and muon neutrino (νμ⏎) The third generation consist of the tau (τ−⏎) and the tau neutrino (ντ⏎). Each type of neutrino is associated with

Steering

Push this neuron up or down while the model writes, and watch what changes. The outputs were generated ahead of time, so nothing runs in your browser.

turned down a lot
Prompt

Here is something I have been thinking about lately: The polononore polononore polononore polononore polononore polononore polononore polononore polononore polononore polononore polonon

Most negative on

Where the activation went furthest below zero. Blue marks negative activation. Many neurons mean something different in each direction.

  1. #1 peak

    learn how to obtain the Java Development Kit (JDK)⏎and write your first Java program.⏎Next, it's on to the Java fundamentals, including data types,⏎operators, control statements, classes, objects, and methods.⏎You'll then progress

  2. #2 peak

    -like?<|endoftext|>& Tornado Alley⏎Jan Mikusinski developed an operational calculus which is relevant for solving differential equations. His operational calculus is based upon an algebra of the convolution of functions with respect to the Fourier transform. From the convolution product he

  3. #3 peak

    , which begins with the study of functions and their derivatives and integrals⏎- The fundamentals of advanced algebra, which is based on axiomatic systems involving operations of addition and multiplication in general settings⏎- Additional subjects such as geometry, probability,

  4. #4 peak

    and develop an understanding of the general principles and characteristics of programming and programming languages. This includes:⏎- algorithms and problem solving with an emphasis on fundamental data structures⏎- object-oriented programming⏎- event-driven programming.⏎At least some portion of a study

Connections

Show on map

Which neurons in earlier layers feed this one, and which later ones it feeds. Amber links excite, blue links suppress; longer bars are stronger.

Fed by earlier layers

  1. L5:78 excites
  2. L10:276 excites
  3. L20:293 suppresses
  4. L5:2 suppresses
  5. L10:291 suppresses
  6. L3:105 excites
  7. L25:26 weakly suppresses
  8. L20:244 weakly excites
  9. L18:408 weakly excites
  10. L3:63 weakly excites
  11. L22:371 weakly excites
  12. L25:69 weakly excites
  13. L17:133 weakly excites
  14. L17:954 weakly suppresses
  15. L25:652 weakly suppresses
  16. L4:352 weakly suppresses
  17. L20:275 weakly excites
  18. L7:334 weakly excites
  19. L23:159 weakly excites
  20. L20:97 weakly excites
  21. L0:839 weakly suppresses
  22. L21:128 weakly excites
  23. L11:75 weakly suppresses
  24. L3:2248 weakly excites

Feeds later layers

  1. L27:111 weakly excites
  2. L27:2101 weakly excites
  3. L27:1048 weakly suppresses
  4. L27:2939 weakly excites
  5. L27:1213 weakly suppresses
  6. L27:971 weakly excites
  7. L27:70 weakly excites
  8. L27:1107 weakly excites
  9. L27:2532 weakly suppresses
  10. L27:2893 weakly excites
  11. L27:125 weakly excites
  12. L27:230 weakly suppresses
  13. L27:1097 weakly excites
  14. L27:2727 weakly suppresses
  15. L27:1725 weakly suppresses
  16. L27:1585 weakly excites
  17. L27:2085 weakly excites
  18. L27:1191 weakly excites
  19. L27:1554 weakly excites
  20. L27:3057 weakly excites
  21. L27:2927 weakly excites
  22. L27:2451 weakly excites
  23. L27:2968 weakly excites
  24. L27:757 weakly excites

Activation histogram

How often this neuron fires at each strength. Almost always it does close to nothing (the tall bars in the middle); the snippets above are the rare moments it fired hard, amber for positive and blue for negative.

1 values between -27.50 and -25.941 values between -19.71 and -18.152 values between -16.60 and -15.042 values between -15.04 and -13.484 values between -13.48 and -11.925 values between -11.92 and -10.3611 values between -10.36 and -8.8114 values between -8.81 and -7.2529 values between -7.25 and -5.6940 values between -5.69 and -4.1397 values between -4.13 and -2.58290 values between -2.58 and -1.023077 values between -1.02 and 0.54240 values between 0.54 and 2.1048 values between 2.10 and 3.6626 values between 3.66 and 5.2113 values between 5.21 and 6.774 values between 6.77 and 8.331 values between 8.33 and 9.891 values between 9.89 and 11.451 values between 11.45 and 13.001 values between 33.26 and 34.81offnegativepositiveoften

Logit lens

The words this neuron nudges the model toward (amber) or away from (blue) when it fires. A hint, not a label: many neurons work through later layers instead.

Promotes

  1. rams
  2. unction
  3. (stats
  4. argument
  5. 积分
  6. ParameterValue
  7. _arguments
  8. (vars
  9. RefCount
  10. -character

Suppresses

  1. чная
  2. riz
  3. pol
  4. 缮
  5. .pol
  6. advis
  7. nâ
  8. ural
  9. 不开
  10. Indo